Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020

The standard 12-lead ECG has been widely used to diagnose a variety of cardiac
abnormalities such as cardiac arrhythmias and predicts cardiovascular
morbidity and mortality. The early and correct diagnosis of cardiac
abnormalities can increase the chances of successful treatments. However,
manual interpretation of the electrocardiogram is time-consuming and requires
skilled personnel with a high degree of training. Automatic detection and
classification of cardiac abnormalities can assist physicians in the diagnosis
of the growing number of ECGs recorded. The PhysioNet/Computing in Cardiology
Challenge 2020 provides an opportunity to address this problem by providing
data from a wide set of sources.

Please see <https://physionetchallenges.github.io/2020/> for all information
about this year's Challenge. We are using the above GitHub Pages link and
Google Groups to post all updates this year. At the end of the Challenge, the
current page will be updated to reflect the complete event and the final
results.